code: def test_explain_smoke_titanic():
      titanic = load_titanic()
      titanic_clean = clean(titanic)
      sc = SimpleClassifier().fit(titanic_clean, target_col="survived")
      explain(sc)
      X, y = (
          titanic_clean.drop("survived", axis=1),
          titanic_clean.survived,
      )
      ep = EasyPreprocessor()
      preprocessed = ep.fit_transform(X)
      tree = DecisionTreeClassifier().fit(preprocessed, y)
      explain(tree, feature_names=ep.get_feature_names_out())
      pipe = make_pipeline(EasyPreprocessor(), LogisticRegression())
      pipe.fit(X, y)
      explain(pipe, feature_names=pipe[0].get_feature_names_out())
  
file_path: dabl/dabl/tests/test_explain.py
imports: import pytest
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.pipeline import make_pipeline
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from dabl.datasets import load_titanic
  from dabl import SimpleClassifier, EasyPreprocessor, explain, clean
label_desc: Use image node_id 1 for calling a global function with example usage: test_explain_smoke_titanic() without return types